The Translation Problem: Evidence Requirements and Stakeholder Variation in Educational AI Governance

Abstract

Memorandum No. 1 documented the operational gap in AI governance frameworks for education: the absence of implementation infrastructure despite abundant principles and regulatory requirements. Memorandum No. 2 examined the forcing functions now closing that gap through insurance exclusions, regulatory timelines, and liability exposure. This memorandum addresses the translation layer: the problem of converting governance commitments into the specific evidentiary formats that different stakeholders require. The same governance domain produces different documentation demands depending on whether an insurer, regulator, procurement authority, or board is asking. Aspirational frameworks describe what institutions should value; insurance questionnaires specify what institutions must produce. The resulting fragmentation means an institution can hold an AI policy that simultaneously satisfies its board, fails its insurer's supplemental application, meets state guidance, and stalls vendor procurement. The governance exists; the translation does not.This memorandum analyzes evidence requirements across four critical domains: transparency and explainability, third-party vendor management, human oversight protocols, and bias testing. It establishes a parallel between the current fragmented state of AI governance assurance and cybersecurity before SOC 2 provided a shared attestation language, suggesting a multi-year trajectory toward standardization. It maps the binding requirements arriving in 2026, including Verisk endorsement availability in January, Colorado CAIA enforcement in June, and EU AI Act high-risk obligations in August, and examines what interim infrastructure institutions require to navigate non-harmonized requirements. The analysis concludes that translation capacity, whether built internally or engaged externally, is necessary during the period when standards have not converged and institutions must nevertheless demonstrate governance to multiple stakeholders with different evidence languages

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